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      <h1 id="Mysql-16-索引覆盖和索引下推"><a href="#Mysql-16-索引覆盖和索引下推" class="headerlink" title="Mysql-16-索引覆盖和索引下推"></a>Mysql-16-索引覆盖和索引下推</h1><h2 id="前言"><a href="#前言" class="headerlink" title="前言"></a>前言</h2><ul>
<li>数据表结构如下：</li>
</ul>
<figure class="highlight plain"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br><span class="line">8</span><br><span class="line">9</span><br><span class="line">10</span><br><span class="line">11</span><br></pre></td><td class="code"><pre><span class="line">create table user (</span><br><span class="line">    id int primary key,</span><br><span class="line">    name varchar(20),</span><br><span class="line">    sex varchar(5),</span><br><span class="line">    index(name)</span><br><span class="line">)engine&#x3D;innodb;</span><br><span class="line"></span><br><span class="line"># 接下来两个查询是截然不同的</span><br><span class="line">select id,name where name&#x3D;&#39;shenjian&#39;</span><br><span class="line"> </span><br><span class="line">select id,name,sex where name&#x3D;&#39;shenjian&#39;</span><br></pre></td></tr></table></figure>

<p><strong>多查询了一个属性，为何检索过程完全不同？</strong></p>
<p>　1. 　<strong>什么是回表查询？</strong></p>
<p>　2. 　<strong>什么是索引覆盖？</strong></p>
<p>　3. 　<strong>如何实现索引覆盖？</strong></p>
<p><strong>哪些场景，可以利用索引覆盖来优化SQL？</strong></p>
<p>PS： <em>本文试验基于MySQL5.6-InnoDB。</em></p>
<a id="more"></a>



<h2 id="1-回表查询"><a href="#1-回表查询" class="headerlink" title="1. 回表查询"></a>1. 回表查询</h2><p>这先要从<code>InnoDB</code>的索引实现说起，<code>InnoDB</code>有两大类索引：</p>
<ul>
<li>聚集索引(<code>clustered index</code>)</li>
<li>普通索引(<code>secondary index</code>)</li>
</ul>
<p><strong>InnoDB聚集索引和普通索引有什么差异？</strong></p>
<ul>
<li>InnoDB<strong>聚集索引</strong>的叶子节点存储行记录，因此， InnoDB必须要有，且只有一个聚集索引：</li>
</ul>
<ol>
<li>关于聚集索引有如下特性：</li>
</ol>
<p>（1）如果表定义了PK，则PK就是聚集索引；</p>
<p>（2）如果表没有定义PK，则第一个<code>not NULL unique</code>列是聚集索引；</p>
<p>（3）否则，<code>InnoDB</code>会创建一个隐藏的<code>row-id</code>作为聚集索引；</p>
<p><em>画外音：所以PK查询非常快，直接定位行记录。</em></p>
<ol start="2">
<li><strong>普通索引又叫做非聚集索引：存放主键值</strong></li>
</ol>
<figure class="highlight plain"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br><span class="line">8</span><br><span class="line">9</span><br><span class="line">10</span><br><span class="line">11</span><br><span class="line">12</span><br><span class="line">13</span><br><span class="line">14</span><br><span class="line">15</span><br><span class="line">16</span><br></pre></td><td class="code"><pre><span class="line">举个栗子，不妨设有表：</span><br><span class="line"></span><br><span class="line">　　t(id PK, name KEY, sex, flag);</span><br><span class="line"></span><br><span class="line">画外音：id是聚集索引，name是普通索引。</span><br><span class="line"></span><br><span class="line"></span><br><span class="line">表中有四条记录：</span><br><span class="line"></span><br><span class="line">　　1, shenjian, m, A</span><br><span class="line"></span><br><span class="line">　　3, zhangsan, m, A</span><br><span class="line"></span><br><span class="line">　　5, lisi, m, A</span><br><span class="line"></span><br><span class="line">　　9, wangwu, f, B</span><br></pre></td></tr></table></figure>

<p><img src="http://zhuuu-bucket.oss-cn-beijing.aliyuncs.com/img/20200922/202123097.png" alt="mark"></p>
<p>两个B+树索引分别如上图：</p>
<ul>
<li>id为PK，聚集索引，叶子节点存储行记录；</li>
<li>name为KEY，普通索引，叶子节点存储PK值，即id；</li>
</ul>
<p>既然从普通索引无法直接定位行记录，那<strong>普通索引的查询过程是怎么样的呢？</strong></p>
<ul>
<li><strong>回表查询因此出现了</strong></li>
<li>通常情况下，需要扫码两遍索引树。</li>
</ul>
<p>例如：</p>
<figure class="highlight plain"><table><tr><td class="gutter"><pre><span class="line">1</span><br></pre></td><td class="code"><pre><span class="line">select * from t where name&#x3D;&#39;lisi&#39;;</span><br></pre></td></tr></table></figure>

<p><strong>是如何执行的呢？</strong></p>
<p><img src="http://zhuuu-bucket.oss-cn-beijing.aliyuncs.com/img/20200922/202248321.png" alt="mark"></p>
<p>如<strong>粉红色</strong>路径，需要扫码两遍索引树：</p>
<p>（1）先通过普通索引定位到主键值id=5；</p>
<p>（2）在通过聚集索引定位到行记录；</p>
<p>这就是所谓的<strong>回表查询</strong>，先定位主键值，再定位行记录，它的性能较扫一遍索引树更低。</p>
<h2 id="2-索引覆盖"><a href="#2-索引覆盖" class="headerlink" title="2. 索引覆盖"></a>2. 索引覆盖</h2><ol>
<li><strong>什么是索引覆盖(Covering index)？</strong></li>
</ol>
<ul>
<li>借用一下SQL-Server官网的说法。</li>
</ul>
<p><img src="http://zhuuu-bucket.oss-cn-beijing.aliyuncs.com/img/20200922/202458539.png" alt="mark"></p>
<ul>
<li>MySQL官网，类似的说法出现在explain查询计划优化章节，即explain的输出结果Extra字段为<strong>Using index</strong>时，能够触发索引覆盖。</li>
</ul>
<p><img src="http://zhuuu-bucket.oss-cn-beijing.aliyuncs.com/img/20200922/202522480.png" alt="mark"></p>
<p>不管是SQL-Server官网，还是MySQL官网，都表达了：<strong>只需要在一棵索引树上就能获取SQL所需的所有列数据，无需回表，速度更快。</strong></p>
<ol start="2">
<li><strong>如何实现索引覆盖？</strong></li>
</ol>
<ul>
<li>常见的方法是：<strong>将被查询的字段，建立到联合索引里去。</strong></li>
</ul>
<p>仍是之前中的例子：</p>
<figure class="highlight plain"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br></pre></td><td class="code"><pre><span class="line">create table user (</span><br><span class="line">    id int primary key,</span><br><span class="line">    name varchar(20),</span><br><span class="line">    sex varchar(5),</span><br><span class="line">    index(name)</span><br><span class="line">)engine&#x3D;innodb;</span><br></pre></td></tr></table></figure>



<ul>
<li>第一个SQL语句：　<code>select</code> <code>id,name</code> <code>from</code> <code>user</code> <code>where</code> <code>name=&#39;shenjian&#39;;</code></li>
</ul>
<p><img src="http://zhuuu-bucket.oss-cn-beijing.aliyuncs.com/img/20200922/202917251.png" alt="mark"></p>
<p>能够命中name索引，索引叶子节点存储了主键id，通过name的索引树即可获取id和name，无需回表，符合索引覆盖，效率较高。</p>
<p><em>画外音，Extra：<strong>Using index</strong>。</em></p>
<ul>
<li>第二个SQL语句： <code>select</code> <code>id,name,sex from</code> <code>user</code> <code>where</code> <code>name=&#39;shenjian&#39;;</code></li>
</ul>
<p><img src="http://zhuuu-bucket.oss-cn-beijing.aliyuncs.com/img/20200922/203020049.png" alt="mark"></p>
<p>能够命中name索引，索引叶子节点存储了主键id，但sex字段必须回表查询才能获取到，不符合索引覆盖，需要再次通过id值扫码聚集索引获取sex字段，效率会降低。</p>
<p><em>画外音，Extra：<strong>Using index condition</strong>。</em></p>
<ul>
<li><strong>如果把(name)单列索引升级为联合索引(name, sex)就不同了。</strong></li>
</ul>
<figure class="highlight plain"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br></pre></td><td class="code"><pre><span class="line">create table user (</span><br><span class="line">    id int primary key,</span><br><span class="line">    name varchar(20),</span><br><span class="line">    sex varchar(5),</span><br><span class="line">    index(name, sex)</span><br><span class="line">)engine&#x3D;innodb;</span><br></pre></td></tr></table></figure>

<p><img src="http://zhuuu-bucket.oss-cn-beijing.aliyuncs.com/img/20200922/203205054.png" alt="mark"></p>
<p><strong>可以看到：都能够命中索引覆盖，无需回表。</strong></p>
<p><em>画外音，Extra：<strong>Using index</strong>。</em></p>
<h2 id="3-索引覆盖的场景"><a href="#3-索引覆盖的场景" class="headerlink" title="3. 索引覆盖的场景"></a>3. 索引覆盖的场景</h2><p><strong>场景1：全表count查询优化</strong></p>
<p><img src="http://zhuuu-bucket.oss-cn-beijing.aliyuncs.com/img/20200922/203321222.png" alt="mark"></p>
<p>原表为：</p>
<p><em>user(PK id, name, sex)；</em></p>
<ul>
<li><p>如果直接<code>select</code> <code>count(name) from</code> <code>user;</code>不能利用索引覆盖。</p>
</li>
<li><p>添加索引：<code>alter</code> <code>table</code> <code>user</code> <code>add</code> <code>key(name);</code>   就能够利用索引覆盖提效。</p>
</li>
</ul>
<p><strong>场景2：列查询回表优化</strong></p>
<figure class="highlight plain"><table><tr><td class="gutter"><pre><span class="line">1</span><br></pre></td><td class="code"><pre><span class="line">select&#96; &#96;id,&#96;&#96;name&#96;&#96;,sex ... &#96;&#96;where&#96; &#96;name&#96;&#96;&#x3D;&#96;&#96;&#39;shenjian&#39;&#96;&#96;;</span><br></pre></td></tr></table></figure>

<ul>
<li>这个例子不再赘述，将单列索引(name)升级为联合索引(name, sex)，即可避免回表。</li>
</ul>
<p><strong>场景3：分页查询</strong></p>
<figure class="highlight plain"><table><tr><td class="gutter"><pre><span class="line">1</span><br></pre></td><td class="code"><pre><span class="line">select&#96; &#96;id,&#96;&#96;name&#96;&#96;,sex ... &#96;&#96;order&#96; &#96;by&#96; &#96;name&#96; &#96;limit 500,100;</span><br></pre></td></tr></table></figure>

<ul>
<li>将单列索引(name)升级为联合索引(name, sex)，也可以避免回表。</li>
</ul>
<h2 id="4-索引下推"><a href="#4-索引下推" class="headerlink" title="4. 索引下推"></a>4. 索引下推</h2><ul>
<li><p><strong>索引下推</strong>（index condition pushdown ）简称ICP，在<strong>Mysql5.6</strong>的版本上推出，用于优化查询。</p>
</li>
<li><p><strong>在不使用ICP</strong>的情况下，在使用<strong>非主键索引（又叫普通索引或者二级索引）</strong>进行查询时，存储引擎通过索引检索到数据，然后返回给MySQL服务器，服务器然后判断数据是否符合条件 。</p>
</li>
<li><p><strong>在使用ICP的情况</strong>下，如果存在某些被索引的列的判断条件时，MySQL服务器将这一部分判断条件传递给存储引擎，然后由存储引擎通过判断索引是否符合MySQL服务器传递的条件，只有当索引符合条件时才会将数据检索出来返回给MySQL服务器 。</p>
</li>
</ul>
<p><strong>小结：</strong> </p>
<ul>
<li><strong>索引条件下推优化可以减少存储引擎查询基础表的次数（回表次数），也可以减少MySQL服务器从存储引擎接收数据的次数</strong>。</li>
</ul>
<h3 id="4-1-举个例子"><a href="#4-1-举个例子" class="headerlink" title="4.1 举个例子"></a>4.1 举个例子</h3><ul>
<li>在开始之前先先准备一张用户表(user)，其中主要几个字段有：<code>id、name、age、address</code>。建立<strong>联合索引（name，age）</strong>。</li>
<li>假设有一个需求，要求匹配姓名第一个为陈的所有用户，sql语句如下：</li>
</ul>
<p><code>SELECT * from user where  name like &#39;陈%&#39;</code></p>
<ul>
<li>根据 “最佳左前缀” 的原则，这里使用了联合索引（name，age）进行了查询，性能要比全表扫描肯定要高。</li>
<li><strong>问题来了，如果有其他的条件呢？假设又有一个需求，要求匹配姓名第一个字为陈，年龄为20岁的用户</strong>，此时的sql语句如下：</li>
</ul>
<figure class="highlight plain"><table><tr><td class="gutter"><pre><span class="line">1</span><br></pre></td><td class="code"><pre><span class="line">SELECT * from user where  name like &#39;陈%&#39; and age&#x3D;20</span><br></pre></td></tr></table></figure>





<p>这条sql语句应该如何执行呢？下面对Mysql5.6之前版本和之后版本进行分析。</p>
<h3 id="4-2-Mysql5-6之前的版本"><a href="#4-2-Mysql5-6之前的版本" class="headerlink" title="4. 2 Mysql5.6之前的版本"></a>4. 2 Mysql5.6之前的版本</h3><ul>
<li>5.6之前的版本是没有索引下推这个优化的，因此执行的过程如下图：</li>
</ul>
<p><img src="http://zhuuu-bucket.oss-cn-beijing.aliyuncs.com/img/20200922/214616079.png" alt="mark"></p>
<ul>
<li>会忽略age这个字段，直接通过name进行查询，在(name,age)这课树上查找到了两个结果，id分别为2,1，然后拿着取到的id值一次次的回表查询，因此这个过程需要<strong>回表两次</strong>。</li>
</ul>
<h3 id="4-3-Mysql5-6及之后版本"><a href="#4-3-Mysql5-6及之后版本" class="headerlink" title="4.3 Mysql5.6及之后版本"></a>4.3 Mysql5.6及之后版本</h3><ul>
<li>5.6版本添加了索引下推这个优化，执行的过程如下图：</li>
</ul>
<p><img src="http://zhuuu-bucket.oss-cn-beijing.aliyuncs.com/img/20200922/214701758.png" alt="mark"></p>
<ul>
<li>InnoDB并没有忽略age这个字段，而是在索引内部就判断了age是否等于20，对于不等于20的记录直接跳过，因此在(name,age)这棵索引树中只匹配到了一个记录，此时拿着这个id去主键索引树中回表查询全部数据，这个过程只需要<strong>回表一次</strong>。</li>
</ul>
<ul>
<li>当然上述的分析只是原理上的，我们可以实战分析一下，因此陈某装了Mysql5.6版本的Mysql，解析了上述的语句，如下图：</li>
</ul>
<p><img src="http://zhuuu-bucket.oss-cn-beijing.aliyuncs.com/img/20200922/214754104.png" alt="mark"></p>
<ul>
<li>根据explain解析结果可以看出Extra的值为<strong>Using index condition</strong>，表示已经使用了索引下推。</li>
</ul>
<h3 id="4-4-总结"><a href="#4-4-总结" class="headerlink" title="4.4 总结"></a>4.4 总结</h3><ul>
<li>索引下推在<strong>非主键索引</strong>上的优化，可以有效减少回表的次数，大大提升了查询的效率。</li>
<li>关闭索引下推可以使用如下命令，配置文件的修改不再讲述了，毕竟这么优秀的功能干嘛关闭呢：</li>
</ul>
<figure class="highlight plain"><table><tr><td class="gutter"><pre><span class="line">1</span><br></pre></td><td class="code"><pre><span class="line">　　set optimizer_switch&#x3D;&#39;index_condition_pushdown&#x3D;off&#39;;</span><br></pre></td></tr></table></figure>
      
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